Brain
Contents
Brain#
This section presents results of brain MRI data. Below are quantitative T1 values computed using the MP2RAGE and the MTsat methods. These values are averaged within the gray matter and white matter masks.
Code imports#
# Python imports
from IPython.display import clear_output
from pathlib import Path
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', 1000)
pd.set_option('display.colheader_justify', 'center')
pd.set_option('display.precision', 1)
# Import custom tools
from tools.data import Data
from tools.plot import Plot
from tools.stats import Stats
Download data#
data_type = 'brain'
release_version = 'latest'
dataset = Data(data_type)
dataset.download(release_version)
--2023-02-08 17:12:50-- https://github.com/courtois-neuromod/anat-processing/releases/download/r20220921/neuromod-anat-brain-qmri.zip
Resolving github.com (github.com)... 140.82.114.4
Connecting to github.com (github.com)|140.82.114.4|:443... connected.
HTTP request sent, awaiting response...
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T171251Z&X-Amz-Expires=300&X-Amz-Signature=f1e01ea662508140b28941a07f4422b39208d82622442410ec1fb9dd5382152c&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream [following]
--2023-02-08 17:12:51-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T171251Z&X-Amz-Expires=300&X-Amz-Signature=f1e01ea662508140b28941a07f4422b39208d82622442410ec1fb9dd5382152c&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.108.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.110.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 1301347 (1.2M) [application/octet-stream]
Saving to: ‘neuromod-anat-brain-qmri.zip’
0K .......... .......... .......... ........
Archive: neuromod-anat-brain-qmri.zip
inflating: data/brain/neuromod-anat-brain.nextflow.log
inflating: data/brain/results-neuromod-anat-brain-qmri.csv
inflating: data/brain/._results-neuromod-anat-brain-qmri.csv
inflating: data/brain/dag.dot
inflating: data/brain/report.html
inflating: data/brain/dag.png
.. .......... 3% 4.64M 0s
50K .......... .......... .......... .......... .......... 7% 5.92M 0s
100K .......... .......... .......... .......... .......... 11% 21.9M 0s
150K .......... .......... .......... .......... .......... 15% 32.5M 0s
200K .......... .......... .......... .......... .......... 19% 8.72M 0s
250K .......... .......... .......... .......... .......... 23% 38.1M 0s
300K .......... .......... .......... .......... .......... 27% 109M 0s
350K .......... .......... .......... .......... .......... 31% 29.8M 0s
400K .......... .......... .......... .......... .......... 35% 47.9M 0s
450K .......... .......... .......... .......... .......... 39% 9.75M 0s
500K .......... .......... .......... .......... .......... 43% 278M 0s
550K .......... .......... .......... .......... .......... 47% 43.0M 0s
600K .......... .......... .......... .......... .......... 51% 139M 0s
650K .......... .......... .......... .......... .......... 55% 87.1M 0s
700K .......... .......... .......... .......... .......... 59% 66.4M 0s
750K .......... .......... .......... .......... .......... 62% 120M 0s
800K .......... .......... .......... .......... .......... 66% 123M 0s
850K .......... .......... .......... .......... .......... 70% 118M 0s
900K .......... .......... .......... .......... .......... 74% 68.9M 0s
950K .......... .......... .......... .......... .......... 78% 11.1M 0s
1000K .......... .......... .......... .......... .......... 82% 161M 0s
1050K .......... .......... .......... .......... .......... 86% 351M 0s
1100K .......... .......... .......... .......... .......... 90% 70.0M 0s
1150K .......... .......... .......... .......... .......... 94% 155M 0s
1200K .......... .......... .......... .......... .......... 98% 147M 0s
1250K .......... .......... 100% 445M=0.05s
2023-02-08 17:12:51 (25.5 MB/s) - ‘neuromod-anat-brain-qmri.zip’ saved [1301347/1301347]
Load data plot it#
qMRI Metrics#
dataset.load()
fig_gm = Plot(dataset, plot_name = 'brain-1')
fig_gm.title = 'Brain qMRI microstructure measures'
# If you're running this notebook in a Jupyter Notebook (eg, on MyBinder), change 'jupyter-book' to 'notebook'
fig_gm.display('jupyter-book')
Statistics#
White Matter#
stats_wm = Stats(dataset)
stats_wm.build_df('WM')
stats_wm.build_stats_table()
display(stats_wm.stats_table)
| T1 (MP2RAGE) | T1 (MTsat) | MTR | MTsat | |
|---|---|---|---|---|
| intrasubject COV mean [%] | 0.6 | 2.3 | 0.6 | 1.7 |
| intrasubject COV std [%] | 0.2 | 0.8 | 0.1 | 0.5 |
| intersubject mean COV [%] | 1.9 | 3.5 | 0.4 | 2.2 |
Grey Matter#
stats_gm = Stats(dataset)
stats_gm.build_df('GM')
stats_gm.build_stats_table()
display(stats_gm.stats_table)
| T1 (MP2RAGE) | T1 (MTsat) | MTR | MTsat | |
|---|---|---|---|---|
| intrasubject COV mean [%] | 0.4 | 3.1 | 0.8 | 2.7 |
| intrasubject COV std [%] | 0.1 | 1.6 | 0.2 | 1.2 |
| intersubject mean COV [%] | 1.0 | 5.7 | 1.2 | 4.5 |
Diffusion#
data_type = 'brain-diffusion-cc'
release_version = 'latest'
dataset = Data(data_type)
dataset.download(release_version)
--2023-02-08 17:12:53-- https://github.com/courtois-neuromod/anat-processing/releases/download/r20230110/brain-diffusion-cc.zip
Resolving github.com (github.com)... 140.82.114.4
Connecting to github.com (github.com)|140.82.114.4|:443... connected.
HTTP request sent, awaiting response...
Archive: brain-diffusion-cc.zip
inflating: data/brain-diffusion-cc/labels.py
inflating: data/brain-diffusion-cc/._labels.py
inflating: data/brain-diffusion-cc/.DS_Store
inflating: data/brain-diffusion-cc/._.DS_Store
inflating: data/brain-diffusion-cc/labels.ipynb
inflating: data/brain-diffusion-cc/._labels.ipynb
inflating: data/brain-diffusion-cc/corpus_callosum-metrics.csv
inflating: data/brain-diffusion-cc/._corpus_callosum-metrics.csv
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/6e6dd34d-c009-4079-bea8-df5eea106c89?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T171253Z&X-Amz-Expires=300&X-Amz-Signature=ce46897c9062444a1e2f4572452b61c4b0a27137cd6dc4cfb9de9f7c7648a9b9&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-cc.zip&response-content-type=application%2Foctet-stream [following]
--2023-02-08 17:12:53-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/6e6dd34d-c009-4079-bea8-df5eea106c89?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T171253Z&X-Amz-Expires=300&X-Amz-Signature=ce46897c9062444a1e2f4572452b61c4b0a27137cd6dc4cfb9de9f7c7648a9b9&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-cc.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.109.133, 185.199.108.133, 185.199.111.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.109.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 15248 (15K) [application/octet-stream]
Saving to: ‘brain-diffusion-cc.zip’
0K .......... .... 100% 8.93M=0.002s
2023-02-08 17:12:53 (8.93 MB/s) - ‘brain-diffusion-cc.zip’ saved [15248/15248]
dataset.load()
fig_diff = Plot(dataset, plot_name = 'brain-diff-cc')
fig_diff.title = 'Brain qMRI diffusion measures - corpus callosum'
fig_diff.display('jupyter-book')
Statistics#
Genu#
stats_cc1 = Stats(dataset)
stats_cc1.build_df('genu')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
| FA (DWI) | MD (DWI) | RD (DWI) | |
|---|---|---|---|
| intrasubject COV mean [%] | 0.8 | 1.0 | 1.3 |
| intrasubject COV std [%] | 0.3 | 0.6 | 0.6 |
| intersubject mean COV [%] | 4.2 | 6.2 | 10.3 |
Body#
stats_cc1 = Stats(dataset)
stats_cc1.build_df('body')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
| FA (DWI) | MD (DWI) | RD (DWI) | |
|---|---|---|---|
| intrasubject COV mean [%] | 0.6 | 0.7 | 0.7 |
| intrasubject COV std [%] | 0.2 | 0.2 | 0.3 |
| intersubject mean COV [%] | 3.8 | 3.0 | 6.2 |
Splenium#
stats_cc1 = Stats(dataset)
stats_cc1.build_df('splenium')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
| FA (DWI) | MD (DWI) | RD (DWI) | |
|---|---|---|---|
| intrasubject COV mean [%] | 0.6 | 0.7 | 0.8 |
| intrasubject COV std [%] | 0.1 | 0.2 | 0.3 |
| intersubject mean COV [%] | 2.6 | 3.1 | 6.3 |